Conventional power-management schemes typically manage the power usage of a computing device by determining whether, and to what extent, a user is currently using the computing device. While these schemes may provide the most optimal experience for users, such schemes fail to account for the impact of each device on a power grid. For example, when a high number of computing devices simultaneously draw power from a power grid, the collective draw of the computing devices may contribute to spikes on the power grid. Some researchers have even estimated that active computing devices (i.e., computing devices that are not in some form of sleep mode) within a single state may collectively draw as much as 322 Megawatts of power from a regional power grid during peak hours.
Unfortunately, if a high number of computing devices simultaneously draw power from a power grid, the power grid may experience unnecessary strain, resulting in both intentional (e.g., rolling blackouts) and unintentional power outages. As such, the instant disclosure identifies a need for managing the power usage of computing devices based on power-management information from a power grid.